The present invention relates generally to the field of computing, and more specifically, to generating and comparing predictive strengths of predictive data models.
Business analysts generally analyze large volumes of data, resulting in a multitude of predictive data models that may be created to help understand or effectuate a target. For example, a common business target is to increase sales. Predictors, such as customer demographics, purchase history, salesperson experience and compensation, may be used to predict those sales. There are some available methods for generating multiple models based on a given set of data, and other methods for assessing their predictive strength. A linear or generalized linear model may, for example, be developed where predictors can be added or removed one at a time. Such methods may create a number of models of varying sizes, and their focus may be to provide for an optimal or most accurate model using all available predictors. For example, current model predictor selection methods may search for an optimal model by creating a sequence of models leading to the optimal model. Therefore, the number of possible models generally grows exponentially with the number of predictors.